25 citations · 35 across the 3 of their papers we have counts for
3 papers
Leveraging ASIC AI Chips for Homomorphic Encryption
Jianming Tong, Tianhao Huang, Jingtian Dang +9
Homomorphic Encryption (HE) provides strong data privacy for cloud services but at the cost of prohibitive computational overhead. While GPUs have emerged as a practical platform f…
FAB: An FPGA-based Accelerator for Bootstrappable Fully Homomorphic Encryption
Rashmi Agrawal, Leo de Castro, Guowei Yang +5
FHE offers protection to private data on third-party cloud servers by allowing computations on the data in encrypted form. However, to support general-purpose encrypted computation…
Does Fully Homomorphic Encryption Need Compute Acceleration?
Leo de Castro, Rashmi Agrawal, Rabia Yazicigil +4
Fully Homomorphic Encryption (FHE) allows arbitrarily complex computations on encrypted data without ever needing to decrypt it, thus enabling us to maintain data privacy on third-…